Mapping spoken language and cognitive deficits in post-stroke aphasia

Aphasia is an acquired disorder caused by damage, most commonly due to stroke, to brain regions involved in speech and language. While language impairment is the defining symptom of aphasia, the co-occurrence of non-language cognitive deficits and their importance in predicting rehabilitation and recovery outcomes is well documented. However, people with aphasia (PWA) are rarely tested on higher-order cognitive functions, making it difficult for studies to associate these functions with a consistent lesion correlate. Broca's area is a particular brain region of interest that has long been implicated in speech and language production. Contrary to classic models of speech and language, cumulative evidence shows that Broca's area and surrounding regions in the left inferior frontal cortex (LIFC) are involved in, but not specific to, speech production. In this study we aimed to explore the brain-behaviour relationships between tests of cognitive skill and language abilities in thirty-six adults with long-term speech production deficits caused by post-stroke aphasia. Our findings suggest that non-linguistic cognitive functions, namely executive functions and verbal working memory, explain more of the behavioural variance in PWA than classical language models imply. Additionally, lesions to the LIFC, including Broca's area, were associated with non-linguistic executive (dys)function, suggesting that lesions to this area are associated with non-language-specific higher-order cognitive deficits in aphasia. Whether executive (dys)function - and its neural correlate in Broca's area - contributes directly to PWA's language production deficits or simply co-occurs with it, adding to communication difficulties, remains unclear. These findings support contemporary models of speech production that place language processing within the context of domain-general perception, action and conceptual knowledge. An understanding of the covariance between language and non-language deficits and their underlying neural correlates will inform better targeted aphasia treatment and outcomes

Pattern classification approaches for breast cancer identification via MRI: state‐of‐the‐art and vision for the future

Mining algorithms for Dynamic Contrast Enhanced Magnetic Resonance Imaging (DCEMRI) of breast tissue are discussed. The algorithms are based on recent advances in multidimensional signal processing and aim to advance current state‐of‐the‐art computer‐aided detection and analysis of breast tumours when these are observed at various states of development. The topics discussed include image feature extraction, information fusion using radiomics, multi‐parametric computer‐aided classification and diagnosis using information fusion of tensorial datasets as well as Clifford algebra based classification approaches and convolutional neural network deep learning methodologies. The discussion also extends to semi‐supervised deep learning and self‐supervised strategies as well as generative adversarial networks and algorithms using generated confrontational learning approaches. In order to address the problem of weakly labelled tumour images, generative adversarial deep learning strategies are considered for the classification of different tumour types. The proposed data fusion approaches provide a novel Artificial Intelligence (AI) based framework for more robust image registration that can potentially advance the early identification of heterogeneous tumour types, even when the associated imaged organs are registered as separate entities embedded in more complex geometric spaces. Finally, the general structure of a high‐dimensional medical imaging analysis platform that is based on multi‐task detection and learning is proposed as a way forward. The proposed algorithm makes use of novel loss functions that form the building blocks for a generated confrontation learning methodology that can be used for tensorial DCE‐MRI. Since some of the approaches discussed are also based on time‐lapse imaging, conclusions on the rate of proliferation of the disease can be made possible. The proposed framework can potentially reduce the costs associated with the interpretation of medical images by providing automated, faster and more consistent diagnosis

Lesion identification and the effect of lesion on motor mapping after stroke

Stroke is the most common cause of long-term severe disability and the motor system that is most commonly affected in stroke. One of the mechanisms that underlies recovery of motor deficits is reorganization or remapping of functional representations around the motor cortex. This mechanism has been shown in monkeys, but results in human subjects have been variable. In this thesis, I used a database that includes longitudinal behavioral and multimodal imaging data in both stroke patients and healthy controls for two research projects. Firstly, I improved an automatic lesion segmentation method to aid in the identification of the location and extent of the stroke in structural magnetic resonance imaging (MRI) images. I developed a point and click interface that allows for the automatic segmentation as well as selecting lesions generated at different thresholds based on the contrast of the T1 images. Second, I investigated the effect of subcortical strokes on motor representations by measuring changes in the topography of inter-hemispheric resting state functional connectivity (FC) MRI to track changes of the hand representation in the damaged hemisphere shows a higher variation across the medial-lateral axis, suggesting a shift in neighboring body representations along the motor strip. During recovery, however, there is a shift in an anterior-posterior direction suggesting a shift into sensory and premotor regions. Obtaining lesion profile and understanding its effect on the functional connectivity can provide us with useful information on the effects of stroke on brain structure and function, which in turn will help in the prognosis and rehabilitation of stroke patients

Arterial spin labelling shows functional depression of non-lesion tissue in chronic Wernicke’s aphasia

Behavioural impairment post-stroke is a consequence of structural damage and altered functional network dynamics. Hypoperfusion of intact neural tissue is frequently observed in acute stroke, indicating reduced functional capacity of regions outside the lesion. However, cerebral blood flow is rarely investigated in chronic stroke. This study investigated cerebral blood flow in individuals with chronic Wernicke’s aphasia and examined the relationship between lesion, cerebral blood flow and neuropsychological impairment. Arterial spin labelling cerebral blood flow imaging and structural MRIs were collected in 12 individuals with chronic Wernicke’s aphasia and 13 age-matched control participants. Joint independent component analysis (jICA) investigated the relationship between structural lesion and hypoperfusion. Partial correlations explored the relationship between lesion, hypoperfusion and language measures. Joint ICA revealed significant differences between the control and WA groups reflecting a large area of structural lesion in the left posterior hemisphere and an associated area of hypoperfusion extending into grey matter surrounding the lesion. Small regions of remote cortical hypoperfusion were observed, ipsilateral and contralateral to the lesion. Significant correlations were observed between the neuropsychological measures (naming, repetition, reading and semantic association) and the jICA component of interest in the WA group. Additional ROI analyses found a relationship between perfusion surrounding the core lesion and the same neuropsychological measures

Automated Lesion Detection-Based Symptome Mapping In Patients With Sensory Deficits

The human brain is the most complex structure known. With its high number of cells, number of connections and number of pathways it is the source of every thought in the world. It consumes 25% of our oxygen and suffers very fast from a disruption of its supply. An acute event, like a stroke, results in rapid dysfunction referable to the affected area. A few minutes without oxygen and neuronal cells die and subsequently degenerate. Changes in the brains incoming blood flow alternate the anatomy and physiology of the brain. All stroke events leave behind a brain tissue lesion. To rapidly react and improve the prediction of outcome in stroke patients, accurate lesion detection and reliable lesion-based function correlation would be very helpful. With a number of neuroimaging and clinical data of cerebral injured patients this study aims to investigate correlations of structural lesion locations with sensory functions

Mapping spoken language and cognitive deficits in post-stroke aphasia

Aphasia is an acquired disorder caused by damage, most commonly due to stroke, to brain regions involved in speech and language. While language impairment is the defining symptom of aphasia, the co-occurrence of non-language cognitive deficits and their importance in predicting rehabilitation and recovery outcomes is well documented. However, people with aphasia (PWA) are rarely tested on higher-order cognitive functions, making it difficult for studies to associate these functions with a consistent lesion correlate. Broca's area is a particular brain region of interest that has long been implicated in speech and language production. Contrary to classic models of speech and language, cumulative evidence shows that Broca's area and surrounding regions in the left inferior frontal cortex (LIFC) are involved in, but not specific to, speech production. In this study we aimed to explore the brain-behaviour relationships between tests of cognitive skill and language abilities in thirty-six adults with long-term speech production deficits caused by post-stroke aphasia. Our findings suggest that non-linguistic cognitive functions, namely executive functions and verbal working memory, explain more of the behavioural variance in PWA than classical language models imply. Additionally, lesions to the LIFC, including Broca's area, were associated with non-linguistic executive (dys)function, suggesting that lesions to this area are associated with non-language-specific higher-order cognitive deficits in aphasia. Whether executive (dys)function – and its neural correlate in Broca's area – contributes directly to PWA's language production deficits or simply co-occurs with it, adding to communication difficulties, remains unclear. These findings support contemporary models of speech production that place language processing within the context of domain-general perception, action and conceptual knowledge. An understanding of the covariance between language and non-language deficits and their underlying neural correlates will inform better targeted aphasia treatment and outcomes

The prognosis of allocentric and egocentric neglect : evidence from clinical scans

We contrasted the neuroanatomical substrates of sub-acute and chronic visuospatial deficits associated with different aspects of unilateral neglect using computed tomography scans acquired as part of routine clinical diagnosis. Voxel-wise statistical analyses were conducted on a group of 160 stroke patients scanned at a sub-acute stage. Lesion-deficit relationships were assessed across the whole brain, separately for grey and white matter. We assessed lesions that were associated with behavioural performance (i) at a sub-acute stage (within 3 months of the stroke) and (ii) at a chronic stage (after 9 months post stroke). Allocentric and egocentric neglect symptoms at the sub-acute stage were associated with lesions to dissociated regions within the frontal lobe, amongst other regions. However the frontal lesions were not associated with neglect at the chronic stage. On the other hand, lesions in the angular gyrus were associated with persistent allocentric neglect. In contrast, lesions within the superior temporal gyrus extending into the supramarginal gyrus, as well as lesions within the basal ganglia and insula, were associated with persistent egocentric neglect. Damage within the temporo-parietal junction was associated with both types of neglect at the sub-acute stage and 9 months later. Furthermore, white matter disconnections resulting from damage along the superior longitudinal fasciculus were associated with both types of neglect and critically related to both sub-acute and chronic deficits. Finally, there was a significant difference in the lesion volume between patients who recovered from neglect and patients with chronic deficits. The findings presented provide evidence that (i) the lesion location and lesion size can be used to successfully predict the outcome of neglect based on clinical CT scans, (ii) lesion location alone can serve as a critical predictor for persistent neglect symptoms, (iii) wide spread lesions are associated with neglect symptoms at the sub-acute stage but only some of these are critical for predicting whether neglect will become a chronic disorder and (iv) the severity of behavioural symptoms can be a useful predictor of recovery in the absence of neuroimaging findings on clinical scans. We discuss the implications for understanding the symptoms of the neglect syndrome, the recovery of function and the use of clinical scans to predict outcome

Classification Models for Plant Diseases Diagnosis: A Review

Plants are important source of our life. Crop production in a good figure and good quality is important to us. The diagnosis of a disease in a plant can be manual or automatic. But manual detection of disease in a plant is not always correct as sometimes it can be not be seen by naked eyes so an automatic method of detection of plant diseases should be there. It can make use of various artificial intelligence based or machine learning based methods. It is a tedious task as it needs to be identified in earlier stage so that it will not affect the entire crop. Disease affects all species of plant, both cultivated and wild. Plant disease occurrence and infection severity vary seasonally, regarding the environmental circumstances, the kinds of crops cultivated, and the existence of the pathogen. This review attempts to provide an exhaustive review of various plant diseases and its types, various methods to diagnose plant diseases and various classification models used so as to help researchers to identify the areas of scope where plant pathology can be improved